code: def get_test_ts_gaps_data():
      from examples.simple.time_series_forecasting.gapfilling import (
          get_array_with_gaps,
      )
  
      gaps_array = get_array_with_gaps(gap_value=np.nan)
      data_ts_gaps = InputData(
          idx=np.arange(0, len(gaps_array)),
          features=gaps_array,
          target=gaps_array,
          task=Task(
              TaskTypesEnum.ts_forecasting,
              TsForecastingParams(forecast_length=5),
          ),
          data_type=DataTypesEnum.ts,
      )
      return data_ts_gaps
  
imports: from functools import partial
  from typing import Union
  import numpy
  from fedot.api.api_utils.assumptions.assumptions_builder import UniModalAssumptionsBuilder, MultiModalAssumptionsBuilder, AssumptionsBuilder
  from fedot.api.api_utils.assumptions.preprocessing_builder import PreprocessingBuilder
  from fedot.core.data.data import InputData
  from fedot.core.data.multi_modal import MultiModalData
  from fedot.core.pipelines.node import PipelineNode
  from fedot.core.pipelines.pipeline import Pipeline
  from fedot.core.repository.dataset_types import DataTypesEnum
  from fedot.core.repository.operation_types_repository import OperationTypesRepository
  from fedot.core.repository.tasks import TaskTypesEnum, Task, TsForecastingParams
  from fedot.preprocessing.data_types import TableTypesCorrector
  from fedot.preprocessing.preprocessing import DataPreprocessor
  from test.integration.api.test_main_api import get_dataset
  from test.unit.dag.test_graph_utils import graphs_same
  from test.unit.data_operations.test_data_operations_implementations import get_time_series, get_small_regression_dataset
  from test.unit.multimodal.data_generators import get_single_task_multimodal_tabular_data
label_desc: Use image node_id 5 for calling a global function with example usage: get_test_ts_gaps_data() and returns: data_ts_gaps